swshon / dialectID_siam

Dialect identification using Siamese network

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Dialect identification using Siamese network

Siamese network based dimensionality reduction for robust dialect identification (and as well as language recognition)

Requirment

  • Python, tested on 2.7.6 (better with jupyter notebook)
  • Tensorflow

Training Model

  • train_ivector.ipynb : Training siamese neural network model for i-vector feature
  • train_word.ipynb : Training siamese neural network model for word feature
  • train_char.ipynb : Training siamese neural network model for character feature
  • train_phone.ipynb : Training siamese neural network model for phoneme feature

Performance evaluation example of i-vector feature on MGB-3 Test dataset

  • Confusion matrix
EGY GLF LAB MSA NOR
EGY 225 13 37 11 24
GLF 11 178 31 16 12
LAB 43 45 212 14 31
MSA 5 5 10 208 10
NOR 18 9 44 13 267
  • Precision
EGY GLF LAB MSA NOR
0.73 0.72 0.61 0.87 0.76
  • Recall
EGY GLF LAB MSA NOR
0.75 0.71 0.63 0.79 0.78

Overall performance

Accurary : 0.731 Precision : 0.739 Recall : 0.732

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Dialect identification using Siamese network


Languages

Language:Jupyter Notebook 89.5%Language:Python 10.5%